Implementation of a generalized pair hidden Markov chain model (GPHMM) that can be used to compute the probability of alignment between two sequences of nucleotides (e.g., a reference sequence and a noisy sequenced read). The model can be trained on a dataset where the noisy sequenced reads are known to have been sequenced from known reference sequences. If no training sets are available default parameters can be used.
| Version: | 0.99.0 |
| Imports: | Rcpp, parallel, dplyr, Biostrings, stringr, stringi, stats, docopt |
| LinkingTo: | Rcpp |
| Suggests: | testthat, knitr, jsonlite |
| Published: | 2017-10-02 |
| Author: | Fanny Perraudeau [aut, cre], James Bullard [aut] |
| Maintainer: | Fanny Perraudeau <perraudeau.f at gmail.com> |
| License: | Artistic-2.0 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | gphmm results |
| Reference manual: | gphmm.pdf |
| Vignettes: |
gphmm |
| Package source: | gphmm_0.99.0.tar.gz |
| Windows binaries: | r-devel: gphmm_0.99.0.zip, r-release: gphmm_0.99.0.zip, r-oldrel: gphmm_0.99.0.zip |
| OS X El Capitan binaries: | r-release: not available |
| OS X Mavericks binaries: | r-oldrel: gphmm_0.99.0.tgz |
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